We present an exact Bayesian inference method for discrete statistical models, which can
find exact solutions to a large class of discrete inference problems, even with infinite support …

We present an exact Bayesian inference method for inferring posterior distributions encoded
by probabilistic programs featuring possibly unbounded loops. Our method is built on a …

Probabilistic models are an indispensable tool in many scientific fields, from the social and
medical sciences to physics and machine learning. In probabilistic programming, such …

We develop nested automatic differentiation (AD) algorithms for exact inference and
learning in integer latent variable models. Recently, Winner, Sujono, and Sheldon showed …

Modeling the interactions of different population dynamics (eg reproduction, migration)
within a population is a challenging problem that underlies numerous ecological research …

Estimating the size and demographic parameters of animal populations is key to effective
conservation. This is commonly done by using counts of animals made by human observers …